R Developer - AI Training

Compensation

Compensation is competitive and varies based on location, education level, and prior experience.

Role Description

As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis focused content. You will evaluate the reasoning quality and step-by-step problem-solving behind each solution, assess solutions for accuracy, clarity, and adherence to the prompt, identify errors in statistical methodology or data-wrangling workflows, fact-check analytical results, write expert-level explanations and model solutions demonstrating correct use of R, and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, directly contributing to the improvement of premier AI models.

Your Profile

• 2+ years of hands-on experience using R for data analysis, statistics, or data science work.
• Strong proficiency in R programming, data wrangling, functional programming patterns, and reusable functions or packages.
• Solid grounding in applied statistics including regression, inference, and model validation.
• Experience in end-to-end analyses in R with data cleaning, exploratory analysis, modeling, and visualization.
• Familiarity with tidyverse, data.table, and ggplot2.
• Professional experience in data-focused roles such as data scientist, statistician, or quantitative analyst.
• Minimum Bachelor’s degree in a quantitative field.
• Experience using large language models (LLMs) for coding assistance and analysis design.
• Excellent English skills with the ability to document analyses and explain complex statistical ideas.
• Previous experience with AI data training or model evaluation is strongly preferred.

Key Responsibilities

• Develop AI Training Content by creating detailed prompts and responses.
• Optimize AI Performance by evaluating and ranking AI responses.
• Ensure Model Integrity by testing for inaccuracies or biases.

Key skills/competency

• R Programming
• Data Analysis
• Statistics
• Data Wrangling
• LLM
• AI Training
• Model Evaluation
• Tidyverse
• Data Visualization
• Problem-solving